Coverage for mlair/helpers/data_sources/toar_data.py: 63%

1__author__ = "Lukas Leufen" 

2__date__ = "2022-07-05" 

3 

4from . import join, toar_data_v2 

5 

6import requests 

7import pandas as pd 

8from .data_loader import EmptyQueryResult 

9 

10 

11def download_toar(station, toar_stats, sampling, data_origin): 

12 try: 

13 # load data from toar-data (v2) 

14 df_toar, meta_toar = toar_data_v2.download_toar(station, toar_stats, sampling=sampling, data_origin=data_origin) 

15 except (AttributeError, EmptyQueryResult, KeyError, requests.ConnectionError, ValueError, IndexError): 

16 df_toar, meta_toar = None, None 

17 

18 try: 

19 # load join data (toar-data v1) 

20 df_join, meta_join = join.download_join(station_name=station, stat_var=toar_stats, sampling=sampling, 

21 data_origin=data_origin) 

22 except (AttributeError, EmptyQueryResult, KeyError, requests.ConnectionError, ValueError, IndexError): 

23 df_join, meta_join = None, None 

24 

25 # merge both data sources with priority on toar-data v2 

26 if df_toar is not None and df_join is not None: 26 ↛ 27line 26 didn't jump to line 27, because the condition on line 26 was never true

27 df_merged = merge_toar_join(df_toar, df_join, sampling) 

28 meta_merged = meta_toar 

29 else: 

30 df_merged = df_toar if df_toar is not None else df_join 

31 meta_merged = meta_toar if df_toar is not None else meta_join 

32 return df_merged, meta_merged 

33 

34 

35def merge_toar_join(df_toar, df_join, sampling): 

36 start_date = min([df_toar.index.min(), df_join.index.min()]) 

37 end_date = max([df_toar.index.max(), df_join.index.max()]) 

38 freq = {"hourly": "1H", "daily": "1d"}.get(sampling) 

39 full_time = pd.date_range(start_date, end_date, freq=freq) 

40 full_data = df_toar.reindex(full_time) 

41 full_data.update(df_join, overwrite=False) 

42 return full_data